Microbiologically influenced corrosion (MIC) is a complex process that generates economic losses to the industry every year. Corrosion must be managed to prevent a loss of containment of produced fluids to the external environment. MIC management includes the identification of assets with higher MIC risk, which could be influenced by nutrient levels in the system. Assessing biofilms under different nutrient conditions is essential for understanding the impact of flow regime on microbial communities and the subsequent impact on microbial corrosion and on the effectiveness of biocide treatment. This investigation simulates closely oil production systems, which contain piping sections exposed to continuous flow and sections that remain stagnant for long periods. Therefore, the results reported here are useful for MIC management and prevention. Moreover, the complementary methodological approach applied in this investigation highlighted the importance of implementing RNA-based methods for better identification of active microorganisms that survive stress conditions in oil systems.
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Salgar-Chaparro et al. (2020) studied this question.
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